1. Field of the Invention
The present invention relates to pulse compression and pulse generation, in particular for compression or generation of chirp pulses.
2. Discussion of Prior Art
Pulse compression and generation are most commonly used in active sonar and radar applications. Active sonar or radar are used for the purpose of detection of objects by the emission of pulses and monitoring the return of the pulse reflections. It is not known at what point in time the reflected pulse will return and therefore it is necessary to monitor the return signal over the period of time in which the pulse is likely to return. The return signal also contains other elements. These are caused by background noise (marine and electrical), biological noise, mechanical noise and clutter. It is therefore necessary to identify the pulse reflection amongst these. Conventionally, this has been done by one of two methods; simple detection or matched filtering (correlation).
Correlation can be implemented in a number of ways but is computationally expensive operation and its achievement in real time requires a high degree of processing power and demands state of the art, thus expensive, technology.
This produces a filter which is a matched to a particular pulse and is known as a matched filter. A filter is said to be matched to a pulse when the transfer function (F[-t]) is the time reversed function of the pulse (F[t]). The output is said to be the compressed pulse. The width of the compressed pulse is proportional to the inverse of the bandwidth of the pulse and the amplitude is proportional to the duration of the pulse. If a pulse with the unit impulse function is applied to a matched filter input, a pulse, which has a function equivalent to the transfer function of the matched filter will be produced. In this way the matched filter can be used as a signal generator.
Matched filtering can be implemented in two ways, in the frequency domain or in the time domain. In the frequency domain it is implemented by digitizing the signal and then using Fast Fourier transform algorithms which, although efficient, require large amounts of computation for large BT products. Often compromise methods are used which give inaccurate results. In the time domain it is implemented using time delays, finite impulse response [FIR] filters and summation. It can be implemented using analogue techniques which requires a large amount of hardware or by digital algorithms which require large amounts of computation.
There are two major background elements in the return signal which need to be reduced. These are reverberation (a sonar term) or clutter (a radar term) and noise. The amount of clutter is reduced by enlarging the bandwidth. For a single frequency pulse, the bandwidth is proportional to the inverse of the pulse length and therefore, by shortening the pulse length, the bandwidth can be enlarged. The amount of noise is reduced by enlarging the pulse length. These two are in conflict with each other. One solution is to use a chirp waveform, a pulse with varying frequency. The bandwidth of a chirp waveform is the difference between the maximum and minimum frequencies. Therefore a large pulse (to reduce noise) with a large bandwidth (to reduce clutter) can be produced.
Often the techniques of signal processing are restricted by physical and financial constraints. These are weight, size and cost. For instance, the signal processing unit may be situated in a torpedo. Size and weight are therefore critical and must be kept to a minimum. Also, for this particular example, the signal processing unit is used only once before being destroyed and therefore, costs to produce it must also be kept to a minimum. The processing also has to be carried out in real time, which requires greater and faster computation, and therefore more hardware.
This invention aims to provide a means by which signals can be processed using less hardware and computation thus minimising weight, size and cost.